International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems

Different definitions of the concept of a fuzzy semiorder are compared. It is proved that their α-cuts are crisp binary relations that may fail to be Ferrers and semitransitive, in general. Consequently, we analyze the preservation of semiorders when coming back from the fuzzy to the crisp setting using α-cuts. In the final sections, a discussion is developed about the extension to the fuzzy setting of the concept of a threshold of utility discrimination, and its corresponding numerical representability of fuzzy semiorders by means of the representability of their α-cuts as crisp binary relations.

This paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.

We investigate a class of multiagent planning problems termed multiagent expedition, where agents move around an open, unknown, partially observable, stochastic, and physical environment, in pursuit of multiple and alternative goals of different utility. Optimal planning in multiagent expedition is highly intractable. We introduce the notion of conditional optimality, decompose the task into a set of semi-independent optimization subtasks, and apply a decision-theoretic multiagent graphical model to solve each subtask optimally. A set of techniques are proposed to enhance modeling so that the resultant graphical model can be practically evaluated. Effectiveness of the framework and its scalability are demonstrated through experiments. Multiagent expedition can be characterized as decentralized partially observable Markov decision processes (Dec-POMDPs). Hence, this work contributes towards practical planning in Dec-POMDPs.

With respect to multiple attribute group decision making problems with linguistic information of attribute values, a group decision analysis is proposed. Some new aggregation operators are proposed: the 2-tuple linguistic weighted harmonic averaging (TWHA), 2-tuple linguistic ordered weighted harmonic averaging (TOWHA) and 2-tuple linguistic combined weighted harmonic averaging (TCWHA) operator and properties of the operators are analyzed. Then, a method based on the TWHA and TCWHA operators for multiple attribute group decision making is presented. In this approach, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

In this paper, by a definite linear function for ranking symmetric triangular fuzzy numbers, in a Fuzzy Linear Programming problem (FLP) model, we introduced a Fuzzy Degenerate Solution (FDS). In the physical meaning, occurrence of degeneracy in a Fuzzy Minimal Cost Flow Network is investigated. To prevent of falling into Cycling phenomenon in optimization process, we defined two new techniques of Cycling prevention proper to fuzzy environment.

In inter-industry studies, the technical coefficients have been analyzed with different methods in order to recognize those coefficients that can be considered to be important for an economy. Many critics have been posed to the procedures, the most remarkable one being their lack of connectivity with the values of the absolute flows behind the coefficients. In our approach, we define the importance of a technical coefficient as a fuzzy concept, and the grade of importance takes into account those absolute flows. This grade can be considered as a membership function, which is used to define a fuzzy graph associated to the I-O matrix. We apply this new procedure to the Spanish 2000 I-O matrix and compare our results to those reached by classical methods.

The spacecraft attitude control systems are becoming more and more sophisticated with the increasing complex system configurations. This paper investigates the problem of three-axis rigid spacecraft maneuver control. The rigid spacecraft model consisting of the dynamic and kinematics equation is firstly provided. This nonlinear model is converted into a Takagi-Sugeno fuzzy model. Then, based on the parallel distributed compensation scheme, a fuzzy state feedback controller is designed for the obtained T-S fuzzy model with considering the decay rate and input constraints. Next, sufficient conditions for the existence of such a controller are derived in terms of linear matrix inequalities and the controller design is cast into a convex optimization problem subject to linear matrix inequalities constraints, which can be readily solved via Matlab LMI toolbox. At last, a design example shows that the time of spacecraft attitude maneuver is shortened and the input constraint is realized. The simulation results show the effectiveness of the proposed methods.

In this paper, we first examine limitations of fuzzy neural networks. We find the following. (1) If training errors are the main concerns, Spline can perform better than the generalized dynamic fuzzy neural network (GD-FNN). (2) If the model is nonlinear with a disturbance term, the testing error of the GD-FNN is very large. If the model is chaotic with a disturbance term, both the training error and testing error of the GD-FNN are very large. (3) Using a sequential algorithm as in the GD-FNN, we would always be trapped at the local minima rather than the global minimum. In addition, we propose to use the characteristics among moments and fuzzy rules to identify the density function in advance.

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA.